Genetic cardiovascular risk prediction: opportunities and limitations

29 January 2009

Cardiomyopathy (deterioration of the heart muscle) is a frequent cause of heart failure, and mutations in genes encoding sarcomeric proteins have been associated with heritable forms of this condition. One such gene is MYCBP3, which encodes cardiac myosin binding protein C (cMyBP-C). A recent paper in Nature Genetics describes the identification of a common MYBPC3 variant, which may be associated with increased risk of cardiomypathy in South Asian populations, and a possible mechanism by which it contributes to disease pathogenesis [Dhandapany et al. (2009), Nat. Genet. Jan. 18 doi:10.1038/ng.309].

The variant, a 25 base pair (bp) deletion mutation was initially identified in a previous study of South Asian individuals with inherited hypercardiomyopathy (HCM); however, the study concluded that its relation to hypercardiomyopathy was unequivocal. In order to investigate its relation to disease further, Dhandapany et al. undertook a case-control study of 800 cardiomypathy cases (comprising hypertrophic cardiomyopathy, restrictive cardiomyopathy, and dilated cardiomyopathy cases) and 699 healthy controls in two groups. They found a statistically significant number of cardiomyopathy cases were either heterozygous or homozygous for the 25bp deletion. A much smaller proportion of the controls were heterozygous, but none were homozygous for the deletion mutation. The group also analysed the frequency of the mutation in India, through screening 6273 individuals in different geographical locations. This showed that although the deletion was found in all major Indian populations, the frequency was higher in southern and western states. In addition, preliminary studies also seemed to indicate that this mutation is present more in South and South East Asia compared to other regions of the world.

The authors suggest that possession of the MYBPC3 variant, may increase risk of cardiomyopathy due to production of an altered protein leading to minor defects in the heart muscle. Furthermore, they suggest that late-onset cardiomyopathy is initiated by accumulation of this protein; however, there may also be other factors that contribute to increased risk, since this variant does not explain all cases of cardiomyopathy and some individuals who are heterozygous for the mutation do not develop the condition. Although the screening for this variant may allow identification of some South Asians at increased risk of cardiomyopathy, it is thought that it only accounts for around 4% of all cases of cardiomyopathy in South Asians. Moreover, the identification of this mutation in South Asian individuals through screening, would currently not alter the medical advice given, nor will it allow identification of those at risk of heart failure, which can have many other causes. More than 200 rare disease-associated mutations affecting 20 different genes have already been identified, highlighting the complex nature of cardiomyopathy.

The limitation of using genetic factors for risk prediction in cardiovascular disease is also high-lighted in a recent paper in the Annals of Internal Medicine. Paynter et al have examined the use of a polymorphism in chromosome 9p21.3 in predicting risk of cardiovascular disease [Paynter et al (2009) Annals of Internal Medicine 150 (2): 65-72]. The authors evaluated the use of conventional risk factors (e.g. blood pressures, smoking, cholesterol levels) and genetic factors in clinical classification of risk for cardiovascular disease, in 22129 white female health professionals. The women had no chronic disease when they joined the study and were followed over a 10 year period. The researchers found that measurement of a single polymorphism in chromosome 9p21.3 location did not improve global risk prediction, when traditional risk factors were known. An earlier study investigating risk prediction of diabetes also demonstrated the limitations of the inclusion of genetic factors (see previous news). However, the results of the present study are perhaps not that surprising, considering that only the contribution of a single polymorphism was evaluated. Risk prediction based on genetic factors is a complex process requiring knowledge based on the cumulative effects of multiple common risk variants (see previous news). In addition to associations between genetic factors and risk, knowledge about the mechanisms by which they contribute to risk is also needed both for better stratification and, more importantly, for the development of novel treatments.